Abstraction of Repository-Centric ANAlysis (Arcana): A rramework for analysing on file-based datasets "in-place" (i.e. without manual download)
Project description
Abstraction of Repository-Centric ANAlysis (Arcana) is Python framework for “repository-centric” analyses of study groups (e.g. NeuroImaging studies) built on the Pydra dataflow engine.
Arcana interacts closely with a data store (e.g. XNAT repository or BIDS dataset), storing intermediate outputs, along with the parameters used to derive them, for reuse by subsequent analyses.
Analysis workflows are constructed and executed using the Pydra package, and can either be run locally or submitted to HPC schedulers using Pydra’s execution plugins. For a requested analysis output, Arcana determines the required processing steps by querying the repository to check for missing intermediate outputs before constructing the workflow graph.
Documentation
Detailed documentation on Arcana can be found at https://arcana.readthedocs.io
Quick Installation
Arcana can be installed for Python 3 using pip:
$ pip3 install arcana>=2.0b
License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License
Note: For the legacy version of Arcana as described in Close TG, et. al. Neuroinformatics. 2020 18(1):109-129. doi: 10.1007/s12021-019-09430-1 please see https://github.com/MonashBI/arcana-legacy. Conceptually, the legacy version and the versions in this repository (>=2) are similar. However, instead of Nipype, v2 uses the Pydra workflow engine (Nipype’s successor) and the syntax has been rewritten from scratch to make it more streamlined and intuitive.
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